Objective To investigate whether HSP90α could be a sensitive and specific serum biomarker for the diagnosis and progression of lung cancer. Methods In the present study, different secretomic analy-ses on the two human lung adenocarcinoma cell lines CL1-0 and CL1-5 with low and high metastatic poten-tial, respectively, were performed using sodium dodecyl sulfate-polyacrylamide gel electrophoresis and ma-trix-assisted laser desorption/ionization time-of-flight mass spectrometry. The candidate biomarker was con-firmed by Western blotting, and was further analyzed in 224 serum samples including 141 lung cancer, 37 benign pulmonary diseases, as well as 46 healthy individuals using ELISA assay. Results HSP90α was sig-nificantly upregulated in the CM of CL1-5 cells. It was found that the levels of HSP90α were specifically ele-vated in the sera of non-small cell lung cancer compared with other groups. At the cut-off point 0.535 on the receiver operating oharacteristie curve, HSP90α could comparatively discriminate lung cancer from benign lung disease and healthy control groups with sensitivity of 0. 817, specificity 0. 919 and total accuracy 80. 14%. Conclusion HSP90α may be a potential useful serum biomarker for discriminating lung cancer from benign lung diseases and healthy individuals and staging of non-small cell lung cancer.

ObjectiveTo explore the typical syndromes and their characteristic of symptoms and signs with high diagnostic value in patients with metabolic syndrome （MS）. MethodsTraditional Chinese medicine （TCM） diagnostic information was collected from 135 MS patients. Syndrome element differentiation and latent class analysis （LCA） were applied to identify the major TCM syndromes in MS patients. Symptoms were analyzed based on the differentiated syndromes， and a binary logistic regression model was constructed to determine symptoms and signs with high diagnostic value. ResultsA total of 135 MS patients were included， involving 163 symptoms and signs with a total frequency of 1749； twenty-three syndrome elements were extracted， 367 times frequency in total， among which 8 syndrome elements occurred ≥10 times with 323 frequencies （88.01% of the total）. These included location-related elements such as kidney （48 times）， spleen （14 times）， and stomach （14 times）， and nature-related elements such as phlegm （71 times）， yin deficiency （64 times）， dampness （57 times）， heat （42 times）， and qi deficiency （13 times）. Based on LCA， the 135 patients were categorized into two groups distinguished by the syndrome elements of dampness and phlegm， forming the "phlegm-dampness syndrome" as the major syndrome type. Nine high-frequency symptoms and signs associated with the phlegm-dampness syndrome were identified，i.e. obesity （39 times）， greasy coating （38 times）， slippery pulse （33 times）， white coating （31 times）， preference for fatty and heavy foods （30 times）， excessive urination （30 times）， fatigue and lack of strength （29 times）， wiry pulse （25 times）， and dark red tongue （25 times）. A binary logistic regression model was constructed combining these nine symptoms and signs with the LCA classification results， ultimately identifying obesity， greasy coating， fatigue and lack of strength， and white coating as independent factors associated with the phlegm-dampness syndrome in MS patients （P＜0.05）. ConclusionThe major TCM syndrome in MS patients is phlegm-dampness syndrome， and obesity， greasy coating， fatigue and lack of strength， and white coating are the typical symptoms and signs for diagnosing phlegm-dampness syndrome in MS patients.